China?s Trade Imbalances: The Role of FDI

China has been running a large trade surplus with the rest of the world, particularly with the USA and EU. This has caused considerable diplomatic tensions and tremendous pressure on the Chinese currency. Existing analytical studies, however, mostly focus on real exchange rate and income as determinants of China?s trade imbalances. Little attention has been given to the role of inflow and outflow of foreign direct investment (FDI). The purpose of this paper is to fill in this gap in the literature by adding FDI to China?s trade balance model. Fitting aggregate annual data from 1979 to 2007 to SURE (Seemingly Unrelated Regression Equations) and later ARDL (Autoregressive Distributed Lags) models, we find that although outflow FDI does not play an important role in determining Chinese trade flows and trade balance, inflow FDI contribute significantly to Chinese exports and thus its trade surplus with the rest of the world. Interestingly, devaluation of the Chinese currency Yuan is found not to affect Chinese trade balance. We also find that both Chinese income and the income of the world play important roles in Chinese trade imbalance. Finally, we find that Chinese trade imbalance is stable.China, trade balance, FDI, real effective exchange rate

HOW STABLE IS THE DEMAND FOR MONEY IN CHINA?

Different authors have tried to estimate the demand for money in different countries. A common theme of almost all studies since 1987 is the application of cointegration technique. The demand for money in China is no exception and has received some attention by researchers. However, finding of cointegration has been interpreted as a sign of constancy of parameter estimates. In this paper we employ CUSUM and CUSUMSQ tests in conjunction with cointegration analysis to show that both M1 and M2 are cointegrated with their determinants. The results of stability tests reveal that while M1 money demand in China is stable, there is some doubt about stability of M2 money demand.Money Demand, China, Bounds Testing, Stability

Improved support vector clustering algorithm for color image segmentation

Color image segmentation has attracted more and more attention in various application fields during the past few years. Essentially speaking, color image segmentation problem is a process of clustering according to the color of pixels. But, traditional clustering methods do not scale well with the number of training sample, which limits the ability of handling massive data effectively. With the utilization of an improved approximate Minimum Enclosing Ball algorithm, this article develops an fast support vector clustering algorithm for computing the different clusters of given color images in kernel-introduced space to segment the color images. We prove theoretically that the proposed algorithm converges to the optimum within any given precision quickly. Compared to other popular algorithms, it has the competitive performances both on training time and accuracy. Color image segmentation experiments on both synthetic and real-world data sets demonstrate the validity of the proposed algorithm

Learning user-specific latent influence and susceptibility from information cascades

Predicting cascade dynamics has important implications for understanding information propagation and launching viral marketing. Previous works mainly adopt a pair-wise manner, modeling the propagation probability between pairs of users using n^2 independent parameters for n users. Consequently, these models suffer from severe overfitting problem, specially for pairs of users without direct interactions, limiting their prediction accuracy. Here we propose to model the cascade dynamics by learning two low-dimensional user-specific vectors from observed cascades, capturing their influence and susceptibility respectively. This model requires much less parameters and thus could combat overfitting problem. Moreover, this model could naturally model context-dependent factors like cumulative effect in information propagation. Extensive experiments on synthetic dataset and a large-scale microblogging dataset demonstrate that this model outperforms the existing pair-wise models at predicting cascade dynamics, cascade size, and "who will be retweeted".Comment: from The 29th AAAI Conference on Artificial Intelligence (AAAI-2015

Approximate Analytical Periodic Solutions to the Restricted Three-Body Problem with Perturbation, Oblateness, Radiation and Varying Mass

Against the background of a restricted three-body problem consisting of a supergiant eclipsing binary system, the two primaries are composed of a pair of bright oblate stars whose mass changes with time. The zero-velocity surface and curve of the problem are numerically studied to describe the third body's motion area, and the corresponding five libration points are obtained. Moreover,theeffectofsmallperturbations,Coriolisandcentrifugalforces,radiativepressure,andthe oblateness and mass parameters of the two primaries on the third body's dynamic behavior is discussed through the bifurcation diagram. Furthermore, the second- and third-order approximate analytical periodic solutions around the collinear solution point L3 in two-dimensional plane and three-dimensional spaces are presented by using the Lindstedt-Poincaré perturbation method

On leaderless consensus of fractional-order nonlinear multi-agent systems via event-triggered control

The consensus problem of fractional-order multi-agent systems is investigated by eventtriggered control in this paper. Based on the graph theory and the Lyapunov functional approach, the conditions for guaranteeing the consensus are derived. Then, according to some basic theories of fractional-order differential equation and some properties of Mittag–Leffler function, the Zeno behavior could be excluded. Finally, a simulation example is given to check the effectiveness of the theoretical result

Impulsive mean square exponential synchronization of stochastic dynamical networks with hybrid time-varying delays

This paper investigates the mean square exponential synchronization problem for complex dynamical networks with stochastic disturbances and hybrid time-varying delays, both internal delay and coupling delay are considered in the model. At the same time, the coupled time-delay is also probabilistic in two time interval. Impulsive control method is applied to force all nodes synchronize to a chaotic orbit, and impulsive input delay is also taken into account. Based on the theory of stochastic differential equation, an impulsive differential inequality and some analysis techniques, several simple and useful criteria are derived to ensure mean square exponential synchronization of the stochastic dynamical networks. Furthermore, pinning impulsive strategy is studied. An effective method is introduced to select the controlled nodes at each impulsive constants. Numerical simulations are exploited to demonstrate the effectiveness of the theory results in this paper

The Bibliometrics Analysis of Customer Knowledge Management Based on Co-Word Analyses

Customer knowledge management (CKM) is a crucial element in the field of knowledge management. By retrieving journal articles with the descriptor words “customer knowledge management” in WOS database, the author selects 3587 journal papers as the research object, then analyses the papers through bibliometrics. Researches show that the research on CKM is in accordance with Place’s curve, which is valuable to study. The focus in the field of CKM is similar at home and abroad, especially some crossing field. Existing research can be divided into three themes: analyzing and mining customer knowledge management from the theory of technology/process, using customer knowledge to manage from the perspective of comprehensive/holism, sharing and interacting knowledge of enterprise both interiorly and exteriorly from the perspective of target/process